Password Cracking Detection System with Honeyword

Honeywords are the decoy words also known as potential password for a user which, when an attacker enters in the system, it is detected by the honeychecker. Honeyword is a technique that can be successfully used as a guard strategy which can be utilized against stolen secret key records. This technique is honed by putting bogus patterns of passwords inside the record that consist of passwords of authentication server to deceive adversary. Honeywords resemble ordinary, user-selected passwords. Various different password patterns make it troublesome for the attacker that steal a honeyword-laced password file to recognize the true user password and honeyword. (?Honey? is an old term for decoy resources in computing environments). In existing system honeywords (decoy passwords) are used to detect malicious attempter against hashed password database. While considering every single accessible record, the legitimate passwords are stored along with various patterns and different combinations of honeywords in order sense impersonation. While considering runtime scenario, a cyber-attacker hacked the file consisting of hashed passwords, but the attacker cannot make out whether the password that is available is authentic password or the honeyword any specific account. If the attacker tries to enter the dummy (honeyword) credentials, then an alarm will be triggered and that will notify the administrator regarding password file breach. Considering the present scenario of the expenses on the storage requirement for expanding the capacity prerequisite by ample amount, this technique is easy to adopt and implement efficiently to encounter the issues of password file disclosure events. The aim of this research is to study honeyword generation system and techniques and compare the sub tasks using the literatures published in those areas finding out the research gaps in them and to analyses them to make password more secure using security hybrid generation method using triple hashing technique as perfectly flat honeyword gene ration method. The second aim is to make honeywords more realistic to trap adversary easily

Modeling Deception for Cyber Security

In the era of software-intensive, smart and connected systems, the growing power and so- phistication of cyber attacks poses increasing challenges to software security. The reactive posture of traditional security mechanisms, such as anti-virus and intrusion detection systems, has not been sufficient to combat a wide range of advanced persistent threats that currently jeopardize systems operation. To mitigate these extant threats, more ac- tive defensive approaches are necessary. Such approaches rely on the concept of actively hindering and deceiving attackers. Deceptive techniques allow for additional defense by thwarting attackers’ advances through the manipulation of their perceptions. Manipu- lation is achieved through the use of deceitful responses, feints, misdirection, and other falsehoods in a system. Of course, such deception mechanisms may result in side-effects that must be handled. Current methods for planning deception chiefly portray attempts to bridge military deception to cyber deception, providing only high-level instructions that largely ignore deception as part of the software security development life cycle. Con- sequently, little practical guidance is provided on how to engineering deception-based techniques for defense. This PhD thesis contributes with a systematic approach to specify and design cyber deception requirements, tactics, and strategies. This deception approach consists of (i) a multi-paradigm modeling for representing deception requirements, tac- tics, and strategies, (ii) a reference architecture to support the integration of deception strategies into system operation, and (iii) a method to guide engineers in deception mod- eling. A tool prototype, a case study, and an experimental evaluation show encouraging results for the application of the approach in practice. Finally, a conceptual coverage map- ping was developed to assess the expressivity of the deception modeling language created.Na era digital o crescente poder e sofisticação dos ataques cibernéticos apresenta constan- tes desafios para a segurança do software. A postura reativa dos mecanismos tradicionais de segurança, como os sistemas antivírus e de detecção de intrusão, não têm sido suficien- tes para combater a ampla gama de ameaças que comprometem a operação dos sistemas de software actuais. Para mitigar estas ameaças são necessárias abordagens ativas de defesa. Tais abordagens baseiam-se na ideia de adicionar mecanismos para enganar os adversários (do inglês deception). As técnicas de enganação (em português, "ato ou efeito de enganar, de induzir em erro; artimanha usada para iludir") contribuem para a defesa frustrando o avanço dos atacantes por manipulação das suas perceções. A manipula- ção é conseguida através de respostas enganadoras, de "fintas", ou indicações erróneas e outras falsidades adicionadas intencionalmente num sistema. É claro que esses meca- nismos de enganação podem resultar em efeitos colaterais que devem ser tratados. Os métodos atuais usados para enganar um atacante inspiram-se fundamentalmente nas técnicas da área militar, fornecendo apenas instruções de alto nível que ignoram, em grande parte, a enganação como parte do ciclo de vida do desenvolvimento de software seguro. Consequentemente, há poucas referências práticas em como gerar técnicas de defesa baseadas em enganação. Esta tese de doutoramento contribui com uma aborda- gem sistemática para especificar e desenhar requisitos, táticas e estratégias de enganação cibernéticas. Esta abordagem é composta por (i) uma modelação multi-paradigma para re- presentar requisitos, táticas e estratégias de enganação, (ii) uma arquitetura de referência para apoiar a integração de estratégias de enganação na operação dum sistema, e (iii) um método para orientar os engenheiros na modelação de enganação. Uma ferramenta protó- tipo, um estudo de caso e uma avaliação experimental mostram resultados encorajadores para a aplicação da abordagem na prática. Finalmente, a expressividade da linguagem de modelação de enganação é avaliada por um mapeamento de cobertura de conceitos

Authentication and Data Protection under Strong Adversarial Model

We are interested in addressing a series of existing and plausible threats to cybersecurity where the adversary possesses unconventional attack capabilities. Such unconventionality includes, in our exploration but not limited to, crowd-sourcing, physical/juridical coercion, substantial (but bounded) computational resources, malicious insiders, etc. Our studies show that unconventional adversaries can be counteracted with a special anchor of trust and/or a paradigm shift on a case-specific basis. Complementing cryptography, hardware security primitives are the last defense in the face of co-located (physical) and privileged (software) adversaries, hence serving as the special trust anchor. Examples of hardware primitives are architecture-shipped features (e.g., with CPU or chipsets), security chips or tokens, and certain features on peripheral/storage devices. We also propose changes of paradigm in conjunction with hardware primitives, such as containing attacks instead of counteracting, pretended compliance, and immunization instead of detection/prevention. In this thesis, we demonstrate how our philosophy is applied to cope with several exemplary scenarios of unconventional threats, and elaborate on the prototype systems we have implemented. Specifically, Gracewipe is designed for stealthy and verifiable secure deletion of on-disk user secrets under coercion; Hypnoguard protects in-RAM data when a computer is in sleep (ACPI S3) in case of various memory/guessing attacks; Uvauth mitigates large-scale human-assisted guessing attacks by receiving all login attempts in an indistinguishable manner, i.e., correct credentials in a legitimate session and incorrect ones in a plausible fake session; Inuksuk is proposed to protect user files against ransomware or other authorized tampering. It augments the hardware access control on self-encrypting drives with trusted execution to achieve data immunization. We have also extended the Gracewipe scenario to a network-based enterprise environment, aiming to address slightly different threats, e.g., malicious insiders. We believe the high-level methodology of these research topics can contribute to advancing the security research under strong adversarial assumptions, and the promotion of software-hardware orchestration in protecting execution integrity therein